基于ELMAN神经网络的短期风速预测

The Wind Speed Short-term Forecast Analysis Based on the Elman Neural Network Predict Model

为了提高风电场风速短期预测的精确性,本文提出了基于Elman神经网络的预测。首先求出风速时间序列的嵌入维数和延迟时间,进而对混沌风速时间序列进行相空间重构。然后利用Elman神经网络对相空间重构后的风速时间序列进行预测,预测结果表明基于Elman神经网络的预测效果满足了精度要求。本文同时运用BP神经网络进行预测。仿真结果表明,基于ELMAN神经网络的预测模型能够较为准确的进行短期风速的预测,具有很高的工程实际应用意义。

In order to improve the accuracy of short-term wind speed forecast,this paper proposes a Elman neural network model.Reconstruction the phase space of the chaotic wind speed time series by calculating the embedding dimension and the delay time of the wind speed time series.Then the Elman neural network model can be used to forecast the wind speed.The results show the Elman neural network model can meet the accuracy requirements.At the same time,this thesis will use the BP neural network prediction model to forecast the wind speed time series.The simulation results show that the Elman neural network prediction model can be a good short-term wind speed prediction model.So it can be widely used in engineering practice.